Cardiovascular fitness is important in several fields, such as sports, fitness industry, clinical for diagnostic, prognostic and rehabilitation, and self monitoring in asymptomatic individuals. The direct measurement of fitness requires maximal physiological effort, which is associated with a greater risk of cardiovascular events, expensive devices and trained personnel. The indirect estimation of fitness overcomes some of these limitations but still requires to undergo rigorously a specific protocol, takes time and often involves the use of specific equipment (such as lab-bicycles, steps etc.).
U.S. Pat. No. 6,241,684 discloses a device, which is capable of determining the maximum oxygen uptake quantity without the restriction of a large device or requiring troublesome operations to be carried out. The device displays the upper and lower limit values for the pulse rate corresponding to an appropriate exercise intensity, and realizes in a wireless manner by means of optical communications the sending and receiving of information such as pulse wave signals to and from an information processing device which processes pulse wave information. The device is provided with a pulse wave detector for detecting the test subject's pulse waveform; an FFT processor for determining the test subject's heartbeat rate from the pulse waveform; a body motion detector for detecting body motion when the test subject is running; an FFT processor for determining the pitch from body motion during running by the test subject; exercise intensity calculator for determining pitch, the test subject's stride, and the exercise intensity from body motion during running; and a nomogram recorder for recording the relationship indicated by an Astrand-Ryhming nomogram, and determining the maximum oxygen uptake quantity from the heart rate and exercise intensity. The obtained maximum oxygen uptake quantity is divided by the test subject s body weight, to calculate the maximum oxygen uptake quantity per unit body weight. Next, the maximum oxygen uptake quantity and pulse according to sex are determined, and the pulse rate is multiplied by the upper and lower limit value coefficients, to determine the upper limit value and the lower limit value for the pulse rate.
WO 2012/057852 A1 discloses techniques for detecting ischemia and classifying a type of ischemia. Electrograms of cardiac activity are generated and evaluated. Ischemia is detected and classified as benign or malignant based on whether a change of an electrogram metric is detected, or first detected, in an electrogram. The relative timing of the change in the electrogram metric and a change in heart rate or patient activity may also be considered. The system may create a stress test for detecting ischemia by instructing the patient to exercise or increasing the cardiac pacing rate.
EP 2 524 647 A1 discloses a system and method for determining sleep stages of a person. A heart rate and a body movement are detected and classified. Combinations of heart rate class and body movement class are identified and a sleep stage and/or a sleep event of the person is determined based thereon.
EP 2 335 563 A1 discloses a system for processing exercise-related data comprising heart activity sensor and a motion sensor further. The type of exercise the user wishes to carry out is input by the user through a user interface. Based thereon exercise-related information can be calculated.
Altini et al. disclose personalizing energy expenditure estimation using a heart rate normalization factor in order to reduce an energy estimation error and inter-individual variability (“Personalizing energy expenditure estimation using a cardiorespiratory fitness predicate,” 7th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 65-72, 5-8 May 2013). The estimation of said normalization factor is based on a fixed set of parameters comprising the subject's heart rate while lying down resting and walking at different speeds together with anthropometric characteristics.